We further evaluated the surrogate model based interpretability using LIME [1]}. LIME obtains a locally linear approximation of the model's behaviour for a given sample by perturbing it and learning a sparse linear model around it. We focus on AgNews and SST based datasets and obtain interpretability estimates using LIME. Once again, we notice a similar pattern of instability as the other two interpretability methods. In Figure REF  we present our results from the LIME based interpretations with Jaccard distance as the measure. Note that we measure the Jaccard distance over the top \(20\%\)  most influential items. We observe once again that NASWA helps in reducing the instability and results in more consistent interpretations.
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